The environmental impacts of artificial light at night have been a rapidly growing field of global change science in recent years. Yet, light pollution has not achieved parity with other global change phenomena in the level of concern and interest it receives from the scientific community, government and nongovernmental organizations. This is despite the globally widespread, expanding and changing nature of night-time lighting and the immediacy, severity and phylogenetic breath of its impacts. In this opinion piece, we evidence 10 reasons why artificial light at night should be a focus for global change research in the 21st century. Our reasons extend beyond those concerned principally with the environment, to also include impacts on human health, culture and biodiversity conservation more generally. We conclude that the growing use of night-time lighting will continue to raise numerous ecological, human health and cultural issues, but that opportunities exist to mitigate its impacts by combining novel technologies with sound scientific evidence. The potential gains from appropriate management extend far beyond those for the environment, indeed it may play a key role in transitioning towards a more sustainable society.

In this paper, we compare 2015 satellite-derived natural gas (gas) flaring data with the greenhouse gas reduction targets presented by those countries in their nationally determined contributions (NDC) under the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement. Converting from flaring to utilization is an attractive option for reducing emissions. The analysis rates the potential role of reduction of gas flaring in meeting country-specific NDC targets. The analysis includes three categories of flaring: upstream in oil and gas production areas, downstream at refineries and transport facilities, and industrial (e.g., coal mines, landfills, water treatment plants, etc.). Upstream flaring dominates with 90.6% of all flaring. Global flaring represents less than 2% of the NDC reduction target. However, most gas flaring is concentrated in a limited set of countries, leaving the possibility that flaring reduction could contribute a sizeable portion of the NDC targets for specific countries. States that could fully meet their NDC targets through gas flaring reductions include: Yemen (240%), Algeria (197%), and Iraq (136%). Countries which could meet a substantial portion of their NDC targets with gas flaring reductions include: Gabon (94%), Algeria (48%), Venezuela (47%), Iran (34%), and Sudan (33%). On the other hand, several countries with large flared gas volumes could only meet a small portion of their NDC targets from gas flaring reductions, including the Russian Federation (2.4%) and the USA (0.1%). These findings may be useful in guiding national level efforts to meet NDC greenhouse gas reduction targets.

Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using Luojia 1-01 and VIIRS nighttime light imagery, we compared several methods for extracting urban areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) and SVM supervised classification. According to the accuracy assessment, the HSI method using LJ1-01 data had the best performance in urban extent extraction, which presented the largest Kappa Coefficient value, 0.834, among all the results. For the urban areas extracted by VIIRS based HSI method, the largest Kappa Coefficient value was 0.772. In contrast, the largest Kappa Coefficient values obtained by STS method were 0.79 and 0.7512 respectively when using LJ1-01 and VIIRS data, while for SVM method the values were 0.7829 and 0.7486 when using Landsat-LJ and Landsat-VIIRS composite data respectively. The experimented results demonstrated that the utilization of nighttime light imagery can largely improve the accuracy of urban extent extraction and LJ1-01 data, with a higher resolution and more abundant spatial information, can lead to better identification results than its predecessors.

The circadian system regulates physiology and behavior. Acute challenges to the system, such as those experienced during travel across time zones, will eventually result in re-synchronization to the local environmental time cues, but this re-synchronization is oftentimes accompanied by adverse short-term consequences. When such challenges are experienced chronically, adaptation may not be achieved, as for example in the case of rotating night shift workers. The transient and chronic disturbance of the circadian system is most frequently referred to as “circadian disruption”, but many other terms have been proposed and used to refer to similar situations. It is now beyond doubt that the circadian system contributes to health and disease, emphasizing the need for clear terminology when describing challenges to the circadian system and their consequences. The goal of this review is to provide an overview of the terms used to describe disruption of the circadian system, discuss proposed quantifications of disruption in experimental and observational settings with a focus on human research, and highlight limitations and challenges of currently available tools. For circadian research to advance as a translational science, clear, operationalizable, and scalable quantifications of circadian disruption are key, as they will enable improved assessment and reproducibility of results, ideally ranging from mechanistic settings, including animal research, to large-scale randomized clinical trials. This article is protected by copyright. All rights reserved.

Among the most visually compelling images of the whole Earth have been those created using data obtained at night by astronauts or from satellites. The proliferation in use of electric lighting—including from industrial, commercial, municipal, and domestic sources—is striking. It sketches the spatial distribution of much of the human population, outlining a substantial proportion of the world's coastline, highlighting a multitude of towns and cities, and drawing the major highways that connect them. The data embodied in these nighttime images have been used to estimate and map levels of energy use, urbanization, and economic activity. They have also been key in focusing attention on the environmental impacts of the artificial light at night itself. Explicit steps need to be taken to limit these impacts, which vary according to the intensity, spectrum, spatial extent, and temporal dynamics of this lighting.